Efficient on -Demand Operations in Large-Scale Infrastructures

120 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.This dissertation discusses several on-demand operations, challenges associated with them, and system designs that meet these challenges. Specifically, we design and implement techniques for (1) on-demand group monitoring that allows users and administrators of an infrastructure to query and aggregate the up-to-date state of the machines (e.g., CPU utilization) in one or multiple groups, (2) on-demand storage for intermediate data generated by dataflow programming paradigms running in clouds, (3) on-demand Grid scheduling that makes worker-centric scheduling decisions based on the current availability of compute nodes, and (4) on-demand key/value pair lookup that is overlay-independent and perturbation-resistant. We evaluate these on-demand operations using large-scale simulations with traces gathered from real systems, as well as via deployments over real testbeds such as Emulab and PlanetLab.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD